Digital Life-style, Sleep & Stress Well being — Oracle

Which dataset used?

I used a dataset associated to psychological fatigue, life-style, and digital utilization patterns.

How did you analyze or put together the information?

The dataset (sourced from Kaggle) was analyzed by means of a structured knowledge preparation and transformation course of to make sure accuracy and significant insights.

Data Cleaning

• Removed null or inconsistent values in key fields like mental_fatigue_score, gender, and occupation
• Standardized categorical values (e.g., gender labels, occupation names)
• Checked for duplicate information and eradicated them

Data Transformation

• Converted numerical fields into acceptable codecs for evaluation
• Created decile buckets for mental_fatigue_score to research distribution (Low → High)
• Aggregated metrics resembling:
  • Total psychological fatigue rating
  • Average fatigue rating by occupation
  • Notifications obtained per day

Data Modeling

• Established relationships between key dimensions:
  • Gender ↔ Occupation
  • Occupation ↔ Mental fatigue rating
• Structured the information to help slicing and filtering throughout a number of dimensions

Visualization & Analysis

• Used completely different charts to signify insights successfully:
  • Bar charts → Comparison throughout occupations
  • Histogram → Distribution of fatigue scores
  • Stacked visuals → Gender and occupation cut up
  • Decile evaluation → Trend from low to excessive fatigue

Did you utilize Oracle Analytics AI options?

Yes, I utilized Oracle Analytics AI capabilities, together with:

Explain, to determine key drivers of attrition
Auto Insights and AI Assistant for producing insights, which had been additional refined and customised.